An effective robust genetic algorithm based on reduced evaluation

Issue title: Selected Papers from the 13th International Symposium on Applied Electromagnetics and Mechanics (ISEM 2007)

Article type: Research Article

Authors: Maruyama, Takayuki^a | Igarashi, Hajime^a

Affiliations: [a] Graduate School of Information and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo, 060-0814, Japan. Tel.: +81 11 706 6487; Fax: +81 11 706 7670; E-mail: maruyama@em-si.eng.hokudai.ac.jp, igarashi@ssi.ist.hokudai.ac.jp

Abstract: Robust optimization searches for optimal solutions which remain feasible under the effect of uncertainties. The conventional robust optimization, however, often requires great computational cost to find robust solutions. This paper introduces a novel robust optimization method based on genetic algorithm. In this method, individuals with "good" performance are selected and tested for their robustness for reduction of computational time. It is shown that the present method works in shorter time in comparison with the conventional robust optimization.

Keywords: Robust optimization, genetic algorithm, SMES

DOI: 10.3233/JAE-2008-974

Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 28, no. 1-2, pp. 177-185, 2008